TY - GEN
T1 - Image Processing Method for Epidermal Cells Detection and Measurement in Arabidopsis Thaliana Leaves
AU - Forero, Manuel G.
AU - Perdomo, Sammy A.
AU - Quimbaya, Mauricio A.
AU - Perez, Guillermo F.
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - Arabidopsis thaliana is the most important model specie employed for genetic analysis in plants. As it has been extensively proven, the first pair of extended leaves and its cellular and morphological changes during Arabidopsis development, is and accurate model to understand the molecular and physiological events that control cell cycle progression in plants. Nevertheless, cell analysis on leaves depends significantly on images acquired from a microscopy coupled to a drawing tube, where cells are traced by hand for posterior digitalization and analysis. This process is tedious, inaccurate and highly temporally inefficient. A new image processing method for cell detection in leaves of Arabidopsis thaliana is presented. Using complementary image processing techniques, we introduce a good way to obtain the original cell contour shapes, surpassing the limitations given by factors like noise, stomata, blurred edges, and non-uniform illumination. Results show the new methodology minimizes considerably the time of cell detection compared with the microscopy coupled tube method, and produces matching percentages over 80%.
AB - Arabidopsis thaliana is the most important model specie employed for genetic analysis in plants. As it has been extensively proven, the first pair of extended leaves and its cellular and morphological changes during Arabidopsis development, is and accurate model to understand the molecular and physiological events that control cell cycle progression in plants. Nevertheless, cell analysis on leaves depends significantly on images acquired from a microscopy coupled to a drawing tube, where cells are traced by hand for posterior digitalization and analysis. This process is tedious, inaccurate and highly temporally inefficient. A new image processing method for cell detection in leaves of Arabidopsis thaliana is presented. Using complementary image processing techniques, we introduce a good way to obtain the original cell contour shapes, surpassing the limitations given by factors like noise, stomata, blurred edges, and non-uniform illumination. Results show the new methodology minimizes considerably the time of cell detection compared with the microscopy coupled tube method, and produces matching percentages over 80%.
KW - Arabidopsis thaliana
KW - Cell drawings
KW - Epidermal cells image detection
KW - Image analysis method
UR - http://www.scopus.com/inward/record.url?scp=85076107582&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-31321-0_36
DO - 10.1007/978-3-030-31321-0_36
M3 - Conference contribution
AN - SCOPUS:85076107582
SN - 9783030313203
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 416
EP - 428
BT - Pattern Recognition and Image Analysis - 9th Iberian Conference, IbPRIA 2019, Proceedings
A2 - Morales, Aythami
A2 - Fierrez, Julian
A2 - Sánchez, José Salvador
A2 - Ribeiro, Bernardete
PB - Springer
T2 - 9th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2019
Y2 - 1 July 2019 through 4 July 2019
ER -